Identification of a methylomics-associated nomogram for predicting overall survival of stage I–II lung adenocarcinoma

Abstract

The aim of this paper was to identify DNA methylation based biomarkers for predicting overall survival (OS) of stage I–II lung adenocarcinoma (LUAD) patients. Methylation profile data of patients with stage I–II LUAD from The Cancer Genome Atlas (TCGA) database was used to determine methylation sites-based hallmark for stage I–II LUAD patients’ OS. The patients were separated into training and validation datasets by using median risk score as cutoff. Univariate Cox, least absolute shrinkage and selection operator (LASSO) and multivariate Cox analyses were employed to develop a DNA methylation signature for OS of patients with stage I–II LUAD. As a result, an 11-DNA methylation signature was determined to be critically associated with the OS of patients with stage I–II LUAD. Analysis of receiver operating characteristics (ROC) suggested a high prognostic effectiveness of the 11-DNA methylation signature in patients with stage I–II LUAD (AUC at 1, 3, 5 years in training set were (0.849, 0.879, 0.831, respectively), validation set (0.742, 0.807, 0.904, respectively), entire TCGA dataset (0.747, 0.818, 0.870, respectively). Kaplan–Meier survival analyses exhibited that survival was significantly longer in the low-risk cohort compared to the high-risk cohort in the training dataset (P = 7e − 07), in the validation dataset (P = 1e − 08), and in the all-cohort dataset (P = 6e − 14). In addition, a nomogram was developed based on molecular factor (methylation risk score) as well as clinical factors (age and cancer status) (AUC at 1, 3, 5 years entire TCGA dataset were 0.770, 0.849, 0.979, respectively). The result verified that our methylomics-associated nomogram had a strong robustness for predicting stage I–II LUAD patients’ OS. Furthermore, the nomogram combined clinical and molecular factors to determine an individualized probability of recurrence for patients with stage I–II LUAD, which stood for a major advance in the field of personalized medicine for pulmonary oncology. Collectively, we successfully identified a DNA methylation biomarker and a DNA methylation-based nomogram to predict the OS of patients with stage I–II LUAD.

Autoencoder-based multimodal prediction of non-small cell lung cancer survival

“…For differentially methylated genes, SEPT9 promoter hypermethylation has been evaluated as a marker for early diagnosis of lung cancer 31 , and its hypermethylation has been associated with poor prognosis in multiple cancer types 32 . Furthermore, in one study in which a methylation nomogram containing 11 probes was created for LUAD prognosis prediction, two of these probes were located in the body of the FAM125B gene (cg12133048, cg13600632) 33 .…”

Methods in DNA methylation array dataset analysis: A review

“…Additionally, Wang et al, 2021 acquired Cox proportional hazard models to select the 11-methylation marker related to the Overall survival (OS) of patients from 485577 methylation sites (samples), being subjected to nomogram construction. This nomogram significantly enhances the predictive capability of the existing predictor for the OS of patients having stage I-II lung adenocarcinoma [143] . Yin et al, 2021 also mentioned the formation of a nomogram model with clinical features and prognostic risk model output, that involves factors to provide accurate prognostic estimates for patients' long-term survival outcomes.…”

“… Cons: Assuming that continuous variables linearly influence the log hazard. [143] 6. 183 periodontitis patient samples and 64 healthy control samples.…”